What if a virtual data layer could be formed over warehouse and lake, and what if the ETL and modeling burden to build that layer were automated, through the use of machine learning? Now the warehouse and lake can exist separately, unified virtually, and interfaced autonomously.
In this webinar you will learn:
How a data warehouse and a data lake can be unified virtually while developing separately
How and when data in the lake can "graduate" to become part of the warehouse
How existing database technologies like views and caching can be applied in new ways to address the new requirements of data-driven organizations
